This project will use the Distributed Ambulatory Research in Therapeutics Network (DARTNet) to assess and improve the accessibility and utility of fulfillment (dispensing) data in community practices. While prescribing data represent what clinicians have prescribed for patients (ideally, the intended prescription medication regimen), fulfillment data represent what patients have received from the pharmacy (ideally, the actual prescription medication regimen). Fulfillment data may help clinicians provide better coordination of care (by revealing what other clinicians have prescribed for a patient) and better informed care (by revealing whether a patient has been able to adhere to prescribed drug regiments). Because fulfillment data represent exposure to medications, they are also very important in observational comparative effectiveness research. Community practices which use fully electronic prescribing (eRx) are obtaining new access to fulfillment data, and federal efforts are actively promoting the adoption of eRx. However, many questions remain about the actual accessibility, comprehensiveness, and utility of these fulfillment data for clinical care and research. DARTNet is uniquely qualified to provide answers for these questions. This AHRQ-funded electronic practice-based network currently includes 32 independent and geographically dispersed organizations encompassing over 1700 clinicians and 4 million patients. It is able to extract, normalize, and aggregate clinical and fulfillment data from these organizations for local interventional research and quality improvement programs in addition to global observational research. For this project, all member practices will first be surveyed for a formal assessment of their use of eRx and the accessibility and utility of fulfillment data in their electronic health records. Fulfillment data will then be extracted from six of those practices. Data will be assessed for comprehensiveness and completeness, and data obtained through eRx will be compared to data obtained through a patient consent process. Estimates of adherence to three classes of medication (antihypertensives, HMG Co-A reductase inhibitors [statins], and antidepressants) will then be derived and compared with benchmark data from published reports. The utility of using prescribing data and fulfillment data to identify unintended continuation and duplication of therapy for anti-hypertensives will also be explored. Using this enriched understanding of the fulfillment data available in community practices, we will develop, refine, and pilot test a hypertension report using clinical and fulfillment data in two practices associated with one DARTNet organization. We will use questionnaires and group interviews to assess the utility of this report and to determine how it may be adapted for other common conditions in primary care. The aims of this project explicitly address AHRQ's interest in health IT to improve the quality and safety of medication management via the integration and utilization of medication management systems and technologies and health IT to improve health care decision making through the use of integrated data and knowledge management.